I'm working with R and have a simple data.frame with two columns. One column is coverage
and the other column is uniqueness
. I need to generate a plot that looks like the one below, where the x-axis is 1:length(df)
and the y-axis is coverage
. I can build that no problem with this simple code, but I need to add a feature where uniqueness
is shown as a gradient along the x-axis. I've tried few things and I think using fill
or scale_colour_gradient()
, should be the answer but it's not working for me.
# barplot
library(ggplot2)
library(graphics)
barplot(df)
# more about barplot() function
?barplot()
EDIT: current plot
dput(newData) structure(list(coverage = c(3.36729582998647, 3.36729582998647, 3.36729582998647, 3.36729582998647, 3.36729582998647, 3.36729582998647, 3.36729582998647, 3.93182563272433, 3.95124371858143, 3.95124371858143, 3.93182563272433, 3.93182563272433, 3.93182563272433, 3.91202300542815, 3.91202300542815, 3.91202300542815, 3.91202300542815, 3.93182563272433, 3.36729582998647, 3.36729582998647, 3.36729582998647, 4.27666611901606, 4.27666611901606, 4.29045944114839, 4.29045944114839, 4.29045944114839, 4.29045944114839, 4.29045944114839, 4.29045944114839, 3.97029191355212, 4.20469261939097, 4.20469261939097, 5.17048399503815, 5.17048399503815, 5.16478597392351, 5.12396397940326, 5.24702407216049, 5.31811999384422, 5.03695260241363, 5.03695260241363, 3.55534806148941, 3.55534806148941, 3.55534806148941, 3.55534806148941, 3.55534806148941, 3.55534806148941, 3.55534806148941, 3.55534806148941, 3.55534806148941, 3.55534806148941, 3.55534806148941, 3.55534806148941, 3.55534806148941, 3.58351893845611, 3.58351893845611, 3.58351893845611, 3.58351893845611, 3.58351893845611, 4.66343909411207, 4.66343909411207, 4.67282883446191, 4.67282883446191, 4.67282883446191, 4.67282883446191, 4.68213122712422, 4.68213122712422, 4.68213122712422, 4.54329478227, 4.52178857704904, 4.52178857704904, 4.52178857704904, 4.52178857704904, 4.52178857704904, 4.52178857704904, 4.52178857704904, 3.71357206670431, 4.18965474202643, 4.47733681447821, 4.47733681447821, 4.51085950651685, 4.51085950651685, 4.52178857704904, 4.53259949315326, 4.53259949315326, 4.55387689160054, 4.56434819146784, 5.23110861685459, 5.2257466737132, 5.2257466737132, 5.22035582507832, 5.2040066870768, 5.20948615284142, 5.2040066870768, 5.2040066870768, 5.29330482472449, 5.28826703069454, 5.28826703069454, 5.31811999384422, 5.31811999384422, 5.31320597904179, 5.30826769740121, 5.31320597904179, 5.39816270151775, 5.39816270151775, 5.39816270151775, 5.5834963087817, 6.10479323241498, 6.10702288774225, 6.10924758276437, 6.10702288774225, 6.10924758276437, 6.11809719804135, 6.1527326947041, 6.1527326947041, 6.19031540585315, 6.14418563412565, 6.18620862390049, 6.18208490671663, 6.18208490671663, 6.16961073249146, 6.20455776256869, 6.22257626807137, 6.22455842927536, 6.23244801655052, 6.2363695902037, 6.27476202124194, 6.27476202124194, 6.27664348934164, 6.22653666928747, 6.23048144757848, 6.23048144757848, 6.25958146406492, 6.26339826259162, 6.33505425149806, 6.33682573114644, 6.33859407820318, 6.34388043412633, 6.34738920965601, 6.3456363608286, 6.36302810354046, 6.361302477573, 6.36302810354046, 6.36818718635049, 6.36990098282823, 6.35088571671474, 6.35437004079735, 6.35610766069589, 6.35610766069589, 6.36647044773144, 6.31716468674728, 6.32076829425058, 6.32256523992728, 6.32256523992728, 6.31896811374643, 6.23441072571837, 6.23441072571837, 6.25190388316589, 6.21060007702465, 6.20657592672493, 6.27476202124194, 6.27287700654617, 6.27287700654617, 6.2709884318583, 6.26909628370626, 6.26339826259162, 6.26339826259162, 6.25766758788264, 6.22257626807137, 6.19440539110467, 6.28226674689601, 6.28226674689601, 6.28226674689601, 6.29156913955832, 6.29526600143965, 11.0455902722788, 11.0605574107758, 11.0683712350503, 11.071750274228, 11.0739397670939, 11.0765732227783, 11.0778873545197, 11.0833110966291, 11.0838334262309, 11.0849539777208, 11.0965005166257, 11.0927172087879, 11.0931737881036, 11.0867626290829, 11.0878034189527, 11.0857974002258, 11.0760935211126, 11.0667477313608, 10.9871723112865, 10.3838436594859, 10.3461842172496, 10.2861956735217, 10.066838635698, 9.62350906446938, 9.59960834518178, 9.58493381641726, 9.55272367519805, 9.55619700847904, 9.55937621211763, 9.56212336983449, 9.5262454033717, 9.51332968849511, 9.5117774096603, 9.46086560003161, 9.45727857185611, 9.45821555950958, 9.45813751072905, 9.45602788772529, 9.44065812703839, 9.38915578944085, 9.33308883723524, 4.30406509320417, 4.30406509320417, 4.29045944114839, 4.27666611901606, 4.27666611901606, 4.27666611901606, 4.27666611901606, 4.27666611901606, 4.27666611901606, 4.30406509320417, 4.31748811353631, 4.30406509320417, 4.31748811353631, 4.31748811353631, 4.29045944114839, 4.29045944114839, 4.29045944114839, 4.29045944114839, 4.29045944114839, 4.30406509320417, 3.91202300542815, 3.87120101090789, 3.85014760171006, 3.29583686600433, 3.29583686600433, 3.29583686600433, 2.94443897916644, 2.94443897916644, 2.94443897916644, 2.94443897916644, 2.94443897916644, 3.80666248977032, 3.80666248977032, 4.40671924726425, 5.91079664404053, 5.90808293816893, 5.84643877505772, 5.31320597904179, 5.16478597392351, 5.17048399503815, 5.17048399503815, 3.25809653802148, 3.25809653802148, 3.25809653802148, 3.25809653802148, 3.25809653802148, 3.25809653802148, 3.25809653802148, 3.25809653802148, 3.25809653802148, 3.29583686600433, 3.29583686600433, 3.29583686600433, 3.29583686600433, 3.29583686600433, 3.29583686600433, 3.29583686600433, 3.29583686600433, 3.29583686600433, 3.29583686600433, 3.29583686600433, 3.29583686600433, 3.29583686600433, 3.29583686600433, 3.29583686600433, 3.29583686600433, 3.29583686600433, 3.29583686600433, 3.29583686600433, 3.29583686600433, 3.29583686600433, 3.29583686600433, 5.14166355650266, 4.9416424226093, 4.79579054559674, 4.78749174278205, 4.78749174278205, 4.78749174278205, 4.66343909411207, 2.07944154167984, 2.07944154167984, 3.61091791264422, 3.61091791264422, 3.61091791264422, 3.61091791264422, 3.63758615972639, 3.63758615972639, 3.63758615972639, 3.63758615972639, 3.63758615972639, 3.66356164612965, 3.66356164612965, 3.66356164612965, 3.66356164612965, 3.66356164612965, 3.66356164612965, 3.66356164612965, 3.66356164612965, 3.66356164612965, 3.66356164612965, 3.66356164612965, 3.66356164612965, 3.68887945411394, 3.68887945411394, 3.68887945411394, 3.68887945411394, 3.68887945411394, 3.68887945411394, 3.68887945411394, 3.68887945411394, 3.71357206670431, 3.71357206670431, 3.71357206670431, 3.71357206670431, 3.71357206670431, 3.71357206670431, 3.71357206670431, 3.71357206670431, 3.71357206670431, 3.71357206670431, 3.71357206670431, 3.71357206670431, 3.71357206670431, 3.71357206670431, 5.00394630594546, 5.00394630594546, 5.01063529409626, 4.95582705760126, 4.70048036579242, 4.85203026391962, 4.85203026391962, 4.85203026391962, 4.85203026391962, 4.85203026391962, 4.85203026391962, 4.85203026391962, 4.84418708645859, 4.83628190695148, 4.83628190695148, 4.83628190695148, 4.83628190695148, 5.30330490805908, 5.84354441703136, 5.8348107370626, 5.83188247728352, 5.82894561761021, 5.82304589548302, 5.82304589548302, 5.82600010738045, 5.76205138278018, 5.76205138278018, 5.82008293035236, 5.8348107370626, 5.83773044716594, 5.84354441703136, 5.84354441703136, 5.84643877505772, 5.85793315448346, 5.85507192220243, 5.85507192220243, 5.97126183979046, 5.98393628068719, 6.04500531403601, 6.03787091992214, 6.04025471127741, 6.08677472691231, 5.46383180502561, 5.54517744447956, 5.54907608489522, 5.54517744447956, 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0.894737, 0.894737, 0.894737, 0.894737, 0.894737, 0.894737, 0.894737, 0.894737, 0.894737, 0.894737, 0.894737, 0.894737, 0.894737, 0.809524, 0.85, 0.85, 0.85, 0.85, 0.107595, 0.107595, 0.103896, 0.104575, 0.104575, 0.103896, 0.102564, 0.102564, 0.101911, 0.101266, 0.101266, 0.100629, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.111888, 0.112676, 0.112676, 0.113475, 0.112676, 0.0226629, 0.022792, 0.0249221, 0.0248447, 0.0243902, 0.0242792, 0.0424403, 0.0424403, 0.0425532, 0.0447368, 0.0447368, 0.0445026, 0.0448549, 0.0445026, 0.0445026, 0.466667, 0.466667, 0.705882, 0.705882, 0.705882, 0.705882, 0.705882, 0.705882, 0.705882, 0.705882, 0.705882, 0.705882, 0.705882, 0.705882, 0.705882, 0.705882, 0.705882, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.923077, 0.923077, 0.923077, 0.0533808, 0.0535714, 0.0528169, 0.714286, 0.714286, 0.789474, 0.789474, 0.866667, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.894737, 0.100592, 0.1, 0.1, 0.0988372, 0.0988372, 0.0994152, 0.0977011, 0.0977011, 0.0982659, 0.0977011, 0.0977011, 0.0971429, 0.0965909, 0.0923913, 0.0923913, 0.0923913, 0.0913978, 0.0913978, 0.0918919, 0.0923913, 0.0918919, 0.0939227, 0.0939227, 0.0939227, 0.9375, 0.941176, 0.941176, 0.941176, 0.941176, 0.941176, 0.941176, 0.941176, 0.941176, 0.941176, 0.941176, 0.941176, 0.941176, 0.941176, 1, 1, 1, 1, 1)), .Names = c("coverage", "uniqueness"), row.names = c(NA, -400L), class = "data.frame")